An extend set-membership filter for state estimation in power systems

Abstract

In order to improve the accuracy and reliability of nonlinear state estimation problems with unknown but bounded noises in power system, an extend set-membership filter for state estimation in power systems is present in this article. The method is based on three sampling sine wave relational model. It overcomes the poor robustness, divergence and weak traceability of kalman filter, avoids the complex calculation process of traditional extend set-membership filter. Compared with kalman filter, the simulation results show that extend set-membership filter algorithm can track signals faster and more accurately.